1. Field of the Invention
This invention relates generally to the field of semiconductor device manufacturing and, more particularly, to a method and system for controlling a process tool.
2. Description of the Related Art
There is a constant drive within the semiconductor industry to increase the quality, reliability and throughput of integrated circuit devices, e.g., microprocessors, memory devices, and the like. This drive is fueled by consumer demands for higher quality computers and electronic devices that operate more reliably. These demands have resulted in a continual improvement in the manufacture of semiconductor devices, e.g., transistors, as well as in the manufacture of integrated circuit devices incorporating such transistors.
Additionally, reducing the defects in the manufacture of the components of a typical transistor also lowers the overall cost per transistor as well as the cost of integrated circuit devices incorporating such transistors.
Generally, a set of processing steps is performed on a group of wafers, sometimes referred to as a xe2x80x9clot,xe2x80x9d using a variety of processing tools, including photolithography steppers, etch tools, deposition tools, polishing tools, rapid thermal processing tools, implantation tools, etc. The technologies underlying semiconductor processing tools have attracted increased attention over the last several years, resulting in substantial refinements. However, despite the advances made in this area, many of the processing tools that are currently commercially available suffer certain deficiencies. In particular, such tools often lack advanced process data monitoring capabilities, such as the ability to provide historical parametric data in a user-friendly format, as well as event logging, real-time graphical display of both current processing parameters and the processing parameters of the entire run, and remote, i.e., local site and worldwide, monitoring. These deficiencies can engender non-optimal control of critical processing parameters, such as throughput, accuracy, stability and repeatability, processing temperatures, mechanical tool parameters, and the like. This variability manifests itself as within-run disparities, run-to-run disparities and tool-to-tool disparities that can propagate into deviations in product quality and performance, whereas an ideal monitoring and diagnostics system for such tools would provide a means of monitoring this variability, as well as providing means for optimizing control of critical parameters.
One technique for improving the operation of a semiconductor processing line includes using a factory wide control system to automatically control the operation of the various processing tools. The manufacturing tools communicate with a manufacturing framework or a network of processing modules. Each manufacturing tool is generally connected to an equipment interface. The equipment interface is connected to a machine interface which facilitates communications between the manufacturing tool and the manufacturing framework. The machine interface can generally be part of an Advanced Process Control (APC) system. The APC system initiates a control script based upon a manufacturing model, which can be a software program that automatically retrieves the data needed to execute a manufacturing process. Often, semiconductor devices are staged through multiple manufacturing tools for multiple processes, generating data relating to the quality of the processed semiconductor devices.
During the fabrication process various events may take place that affect the performance of the devices being fabricated. That is, variations in the fabrication process steps result in device performance variations. Factors, such as feature critical dimensions, doping levels, contact resistance, particle contamination, film optical properties, film thickness, film uniformity, etc., all may potentially affect the end performance of the device. Various tools in the processing line are controlled in accordance with performance models to reduce processing variation. Commonly controlled tools include photolithography steppers, polishing tools, etching tools, and deposition tools. Pre-processing and/or post-processing metrology data is supplied to process controllers for the tools. Operating recipe parameters, such as processing time, are calculated by the process controllers based on the performance model and the metrology information to attempt to achieve post-processing results as close to a target value as possible. Reducing variation in this manner leads to increased throughput, reduced cost, higher device performance, etc., all of which equate to increased profitability.
Metrology data collected after the processing of a wafer or lot of wafers may be used to generate feedback and/or feedforward information for use in determining a control action for the previous process tool (i.e., feedback), the subsequent process tool (i.e., feedforward), or both. Metrology data may also be used by fault detection and classification (FDC) systems employed to detect defective lots or process tools. The collection of metrology data is costly in terms of process delay and resource expenditure. Accordingly, it is generally not feasible to collect metrology data after processing of every lot or after each process step. The fact that metrology data is not collected after every process step is a first source of process control and fault detection inefficiency. The performance of the entire process may not be optimized because metrology data is not collected for every process step.
A lot that is subjected to a metrology step is typically removed from the production flow and transferred to a metrology tool where characteristics of the lot are measured. The collected metrology data may then be used to control the previous or subsequent process tool in the process flow. Typically, there is a significant time period required to complete the metrology cycle of collecting the data and determining a control action based on the metrology data. The delay inherent in the metrology cycle introduces a second source of process control and fault detection inefficiency. During this time period other lots may have been processed using the same process settings as were used on the measured lot. The effectiveness of process control activities is thus reduced due to the lag time associated with implementing automatic control actions resulting from the metrology cycle. The metrology cycle also reduces the effectiveness of FDC systems, because lots processed after a fault condition is present, but before the metrology data can be collected and processed may be in jeopardy.
The present invention is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above.
One aspect of the present invention is seen in a method that includes processing a workpiece in accordance with a first operating recipe. The workpiece is processed in accordance with a second operating recipe subsequent to processing the workpiece in accordance with the first operating recipe. A characteristic of the workpiece is measured after processing in accordance with the second operating recipe. An operating recipe parameter is determined for the first operating recipe based on the measured characteristic.
Another aspect of the present invention is seen in a processing line including first and second process tools, a metrology tool, and a controller. The first process tool is configured to process a workpiece in accordance with a first operating recipe. The second process tool is configured to process the workpiece in accordance with a second operating recipe subsequent to the processing of the workpiece in accordance with the first operating recipe by the first process tool. The metrology tool is configured to measure a characteristic of the workpiece after processing in the second process tool. The controller is configured to determine an operating recipe parameter for the first operating recipe based on the measured characteristic.